Dr. Shuyuan Ho, Assistant Professor at the School of Library and Information Studies (SLIS), Florida’s iSchool, has been awarded a two year grant for $200,000 from the National Science Foundation (NSF).
The grant team will be led by Dr. Ho (Principal Investigator) and includes Dr. Xiuwen Liu (Co-Principal Investigator) and Dr. Mike Burmester (Co-Principal Investigator), both from FSU Computer Science. The team is working in partnership with a leading visionary in online deception research; Dr. Jeffrey Hancock from Cornell Information Science Department.
This collaborative research between Florida State University and Cornell University is to identify language-action features from text-based messages that can be used to dynamically infer a social actor’s perceived trustworthiness. The team will investigate using optimal analysis techniques to calibrate trustworthiness reasoning, which can be used to computationally model actors’ deceptive behaviors in cyber space and to infer actors’ intent based on their words and actions.
According to Dr. Ho, “Cyber infrastructure security is critical to our society, and to national security. With the ubiquitous availability of information technology, the way we communicate online with each other has changed significantly. The existence of online/mobile banking, cloud computing storage, social media, and the wireless network, have all challenged conventional ways of securing information and information systems. We must advance our understanding of cybersecurity beyond technological development, to include our understanding of human motivation, language semantics, and information behavior in complex networks of human computer interaction.”
This research will have a transformative impact in understanding the dynamics of trusting relationships through observing language-action features and psychosocial trustworthiness attribution mechanisms. This study serves as a precursor to a socio-technical schema that will facilitate national security and data protection for the general populace while also protecting the individual’s right to privacy. This study will contribute to the science of cyber-security, and will help the cyber-security community to understand and enable trustworthy communication and collaborative information behavior among computer-mediated groups in a systematic way.
Before joining Florida’s iSchool, Dr. Ho was an Assistant Professor at Drexel University Computing and Security Technology Program. Prior to her faculty role at Drexel, Dr. Ho was a Post-Doctoral Research Associate at the New Jersey Institute of Technology for a digital library research project on IntegraL funded by National Science Digital Library (NSDL) and National Science Foundation (NSF). She earned her Ph.D. in information science and technology from Syracuse University’s iSchool.
Dr. Ho’s research focuses on trusted human-computer interactions, specifically addressing issues of insider threats and online identity theft. Her theory of trustworthiness attribution integrates social psychologies of trust and attribution for insider threat detection as supported by cyber infrastructure. She further develops the framework for a dyadic attribution model to assess human trustworthiness in sophisticated online communication environments. Dr. Ho designs online games as an experimental protocol for investigating human deception in virtual organizations. She founded the iSensor Lab in 2010 – primarily dedicated to socio-technical research on human factors in securing cyberspace. Experiments are conducted live in a virtual laboratory. Research data is collected through confined resources and interactions that are based on real-world cyber trust and deception simulations.
Dr. Ho’s teaching includes computing security, disaster recovery, risk assessment and management, incident response, computer auditing, intrusion detection, organizational behavioral forensics, access control models for intrusion prevention, and information systems management.
For additional grant info, visit: http://www.nsf.gov/awardsearch/showAward?AWD_ID=1347113&HistoricalAwards=false